metadata
base_model: asafaya/bert-base-arabic
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: results
results: []
results
This model is a fine-tuned version of asafaya/bert-base-arabic on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5491
- Accuracy: 0.8431
- F1: 0.8420
- Precision: 0.8419
- Recall: 0.8431
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.581 | 1.0 | 1847 | 0.4896 | 0.8299 | 0.8267 | 0.8316 | 0.8299 |
| 0.3579 | 2.0 | 3694 | 0.4723 | 0.8403 | 0.8376 | 0.8429 | 0.8403 |
| 0.1966 | 3.0 | 5541 | 0.5491 | 0.8431 | 0.8420 | 0.8419 | 0.8431 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2